User-Generated Online Health Content: A Survey of Internet Users in the United Kingdom

Background The production of health information has begun to shift from commercial organizations to health care users themselves. People increasingly go online to share their own health and illness experiences and to access information others have posted, but this behavior has not been investigated at a population level in the United Kingdom. Objective This study aims to explore access and production of user-generated health content among UK Internet users and to investigate relationships between frequency of use and other variables. Methods We undertook an online survey of 1000 UK Internet users. Descriptive and multivariate statistical analyses were used to interpret the data. Results Nearly one-quarter of respondents (23.7%, 237/1000) reported accessing and sharing user-generated health content online, whereas more than 20% (22.2%, 222/1000) were unaware that it was possible to do this. Respondents could be divided into 3 groups based on frequency of use: rare users (78.7%, 612/778) who accessed and shared content less than weekly, users (13.9%, 108/778) who did so weekly, and superusers (7.5%, 58/778) who did so on a daily basis. Superusers were more likely to be male (P<.001) and to be employed (P<.001), but there were no differences between the groups with respect to educational level (P=.99) or health status (P=.63). They were more likely to use the Internet for varied purposes such as banking and shopping (P<.001). Conclusions Although this study found reasonably widespread access of user-generated online health content, only a minority of respondents reported doing so frequently. As this type of content proliferates, superusers are likely to shape the health information that others access. Further research should assess the effect of user-generated online content on health outcomes and use of health services by Internet users.


Figure 1
The  Figure 10.

SUMMARY Background
The Citizen Panel Survey carried out in SIMPHS2 to better assess users and patients' needs and expectations with regard to ICT for health, directly supports the objectives of the Digital Agenda in the area of eHealth which are to both cope with societal challenges and create opportunities for innovation and economic growth by reducing health inequalities, promoting active and healthy ageing and increasing empowerment. It also contributes to the goals of the European Innovation Partnership on Active and Healthy Aging which addresses the societal challenge of an ageing population focusing on the main areas of life events (Prevention, Care and cure and Independent living) with the following expected results:  An improvement of the health status and quality of life of Europeans, especially older people;  An improvement of the sustainability and efficiency of health and social care systems;  Boosted EU competitiveness through an improved business environment for innovation In this policy context the analysis of users' demand undertaken through the SIMPHS2 Citizen panel survey aims to:  develop typologies of digital healthcare users and measure the impact of ICT and the Internet on health status, health care demand and health management.
 identify factors that can enhance or inhibit the role and use of Personal Health Systems from a citizen' s perspective with special emphasis on mHealth, RMT, disease management, Telecare, Telemedicine and Wellness.
To reach these objectives, we started by defining a theoretical framework for policy-making, which was used to design and gather relevant information. A multivariate statistical analysis was subsequently carried out to identify the underlying conceptual dimensions emerging from the data collected. Key relationships between concepts (underlying dimensions) were identified to understand ICT for Health as a complex ecosystem. We concluded with some lessons learned.

Conceptual framework: Towards social determinants of ICT for Health
Two frameworks are at the root of our own conceptual framework "Towards social determinants of ICT for Health". One is the WHO Commission on Social Determinants of Health Framework which summarises how "social, economic and political mechanisms give rise to a set of socioeconomic positions, whereby populations are stratified according to income, education, occupation, gender, race/ethnicity and other factors; these socioeconomic positions in turn shape specific determinants of health status (intermediary determinants) reflective of people's place within social hierarchies; based on their respective social status, individuals experience differences in exposure and vulnerability to health-compromising conditions". While this framework does not relate directly to ICT for Health, the structural determinants perfectly overlap the core argument of personal and positional categories of and distribution of resources in van Dijk's "Causal and Sequential Model of Digital Technology Access by individuals in Contemporary Societies" which is the second framework in which our approach is rooted.
As a result and as illustrated in the next we defined "Towards social determinants of ICT for Health" as follows:  Social determinants of health and health inequalities, therefore structural and intermediary determinants produce different levels of ICT access (motivation, material, skills and usage).
 Unequal access to ICT will generate different levels of ICT for Health access as well as different levels of willingness to use ICT for Health.
 ICT for Health access depends on the properties of ICT and the relationship among Motivation; ICT for Health readiness and Internet Health information.  These impacts could modify both structural and intermediary determinants and distribution of health and well-being.

Social Determinants of Health and ICT for Health conceptual framework
Source: Authors' elaboration based on WHO and van Dijk.

Online panel survey technical information
Based on the above framework, we gathered data through a questionnaire which we designed and structured around five main blocks 1 : It should be noted that the data analysed in this report relates to an Internet user population which also forms part of online panels. Accordingly, it can be deduced that the respondents' profile in terms ICT uses is slightly more advanced than that of the general population of the surveyed countries. However the underlying dimensions identified and their relationship remain valid.

ICT access
With respect to Internet based activities, the sampled population mainly uses it to search for information (68% every day), sending e-mails with attachments (41%), online banking (20%), social networks (39%) and instant messaging (23%). Internet activities are linked with the male gender, the youngest age groups, a university education, self-employment and entrepreneurs, students, population density and a good state of health. These factors represent a social gradient of Internet activities from the easiest use of the Internet (basic uses) to the most sophisticates activities (tech uses).

ICT for Health Motivation
Individuals were asked about the triggers to utilise ICT for Health. More than a third of the sampled European population indicates a significant use of ICTs in health to better understand a health problem or disease (39%), to find additional sources of information (36%) and to develop knowledge and personal satisfaction (35%). A little further behind, but still with a relevant frequency, there is the perception that ICTs in health are very useful to help a family member or a friend who is ill (31%), to prevent illnesses or to adopt a more healthy lifestyle (28%), to find a solution to or a treatment for a health problem (28%), to obtain different points of view about an issue (22%), and to access an online health service (21%). Finally, and as a counterpoint, only 11% of European citizens give much importance to the use of ICTs in health for participating in online discussions.
With respect to the socio-demographic characteristics of the population, the perception of the importance of ICT in health as triggers is much more positive for women, young people, the middle aged, those with a tertiary education, the employed, students, and people in a bad state of health or with long standing illnesses.
From these items two factors have emerged:  social and services oriented, and  individual oriented uses.
Empowerment, broadly understood as the development of personal involvement and responsibility is one of the goals of prevention, promotion and protection in health. This definition assumes that responsibility is a more active form of control while competence refers to aptitudes or qualities that make it possible to be more autonomous and take a role in decision-making. Factor analysis identified these two dimensions of empowerment Moreover, three different perspectives of personal empowerment seem to coexist with respect to Health:  ability to comply with expert advice (professional perspective),  Self-reliance through individual choice (consumer perspective),  Social inclusion through the development of collective support (community perspective).
Overall, this greater digital empowerment for the European citizens when it comes to their health and the healthcare professionals is linked with higher education levels, the worst states of health and the existence of long-standing illnesses Finally, individuals were asked about the barriers to utilise ICT for Health. Lack of privacy (52%), security (51%), reliability (47%) and trust (46%) were the four main barriers for ICT uses for health indicated by the sampled European population to be very important. Other justifications were the lack of liability (38%), health literacy (36%), knowledge (33%), access to ICTs for health (29%), motivation and interest (28%), and the lack of digital skills (24 %).
Firstly, women are much more sensitive to barriers to the ICT use for health than men, particularly in terms of a lack of confidence. Similarly, the perception of barriers to ICT use for health is also much more evident in older people, those with lower levels of education and the inactive. Lastly, it is also worth highlighting that the presence of long standing illnesses is also very sensitive to lack of confidence.
The underlying dimensions of these items are:  Lack of confidence, and  Lack of readiness.
When it comes to specifically using the Internet for health and wellness, the research has provided interesting information, with notable relative differences. The main use of the Internet for health is for individual information searches, rather than sharing information, communicating or interacting about health and more particularly information searches about physical illnesses or conditions.
Over half of the sampled European citizens have never used the Internet to buy medicine or vitamins online (56% of the total); participated in online support groups for people with the same health issue (60%), used social networking sites for health and wellness issues (58%); used e-mail or websites to communicate with a doctor or their office (58%); analysed the privacy policy for personal information in medical websites (52%); explained a medical issue online in order to make contact with an e-health medical service (61%) or with other users (58%); disclosed medical information on social networking sites (67%); or disclosed medical information on websites to share pictures, videos, or movies (67%). With respect to the remaining socio-demographic factors, the analysis shows homogeneity in terms of the overall use of ICT for health, which is more frequent in the young population, those with a tertiary education, students and the employed, those in densely populated urban areas, people in a bad state of health and those with long standing illnesses.
The factor analysis of ICT for health activities reveals two underlying dimensions:  ICT for Health oriented towards Information and Communication, and  ICT for Health oriented towards services and devices.
Finally, these items allow us to analyse individuals' level of awareness, skills and willingness. First of all, individuals were directly asked about their level of awareness. Second, the number of activities carried out by individuals was considered as a proxy for skilled individuals. Third, individuals who stated they never carry out these activities or were not aware of them were asked about their willingness to carry out these activities. The factor analysis of willingness reveals three underlying dimensions:  Willingness to use Internet Health information,  Willingness to use Web 2.0,  Willingness to use services and devices.
These factors are consistent with the underlying dimensions of ICT readiness mentioned before.

ICT for Health Impact
The study has also provided evidence about the consequences of ICT for Health utilisation. It has to be said that the perceptions are positive overall. 58% of the sampled European population state they agree that ICT use for health allows savings in terms of cost of travel and time. 56% state that they would be willing to share personal health information with their doctor despite the privacy issue. 55% state that ICTs for health can improve the possibilities for caring for themselves and monitoring their state of health. 55% agree with the fact that ICT use for health leads to greater patient satisfaction. 54% agree that e-health can improve the quality of the medical services received. 50% of the European citizens consider that ICT use for health can change their behaviour towards a healthy lifestyle.
Slightly under half of the sample of European citizens, 43%, agrees that ICT use for health can improve their state of health. 42% consider that they would feel more comfortable and safe if they used a remote monitoring system for their health condition. 42% consider that ICT use for health increases ICT use in other fields of daily life. 32% agree that the use of health services through the Internet substitutes face-to-face consultations with doctors. 32% agree that online health services and face-to-face services are of equal quality. And lastly, 23% of European citizens would be willing to pay for access to Internet health services to improve their state of health or that of their relatives.
Positive attitudes about the impact of ICT for health are more prominent among the youngest population, those with a tertiary education, and those that live in densely populated areas. The only notable difference between individuals with bad state of health and those with good state of health is the perception by the former that ICT uses for health can improve the quality of health services received (57%). Meanwhile, citizens with long standing illnesses clearly state their favourable perceptions of ICT use for health, as opposed to citizens that do not have long standing illnesses. In particular, they state that ICT use can improve patient satisfaction (56%), improve caring and health condition monitoring skills (57%), save travelling costs and time (60%), and that they are willing to share personal information through the Internet with doctors and health organisations despite privacy issues (60%).
Finally the factor analysis reveals two underlying dimensions:  Impact on quality of healthcare and healthy behaviour,  Impact on healthcare access.
All items gathered were grouped into underlying dimensions through multivariate statistics following our conceptual framework. This exercise allows us to transform items into concepts and therefore understand the complexity of the ICT for Health ecosystem.

Underlying dimensions of Social determinants of ICT for Health
Source: Authors' elaboration.
All above mentioned unveiled the complexity of ICT for Health. To tackle this complexity, correlation analyses of all dimensions have been performed. The main results of these analyses are summarised in the following figure:

Key relationships of Social determinants of ICT for Health
Source: Authors' elaboration.
 Social determinants of Health (structural and intermediary), especially education and age, produces different levels of ICT readiness. Advance uses of the Internet such as Tech and Web 2.0 uses are more likely to be carried out by the young, the healthy and the welleducated population while basic uses are mostly performed by the elderly, therefore individuals with worse health status (chronic patients and individuals having reported higher numbers of health problems).
 Unequal ICT readiness generates different levels of motivation. Individuals making more advance uses are triggered by the potential of ICT to facilitate social interaction and services related to health while individuals whose uses are basic or individual are triggered mainly by Internet health information for personal proposes. Furthermore, individuals with the lowest level of readiness (basic uses) and having reported more health problems lack confidence in the use of ICT for Health. Nevertheless, this lack of confidence is counterbalanced by a higher level of empowerment (competence oriented).
 Both ICT for Health usages (Services and Devices and Information and Communication) are specially driven by social and services triggers while individual triggers are only slightly correlated with Information and Communication usages, therefore less advanced uses.
 Both dimensions of Empowerment push ICT for Health usage. Individuals who are more competence-oriented are more inclined to Information and Communication usage while individuals who are more control-oriented are more likely to use Services and Devices. Thus individuals who feel more responsible for their health status are more likely to use Services and Devices while individuals who want to be more autonomous (competence refers to aptitudes or qualities that make it possible to be more autonomous) are more likely to utilise Information and Communication. If we consider individuals' education, age and health status it looks like Services and Devices are related with well-being and wellness practice, therefore with health prevention and promotion while Information and Communication are more related with illness, therefore with cure and independent living  All individuals using ICT for Health faced the same barriers; therefore lack of confidence and lack of readiness are not correlated significantly with ICT for Health usages. Nevertheless, lack of confidence is negatively correlated with the ICT for Health impact on the access dimension. Individuals need a certain level of confidence in ICT for Health to go beyond information and communication and engage with services such as RMT, Personal Health Records or videoconference consultation.
 The utilisation of Services and devices is strongly correlated with the perception that ICT would have an impact on both healthcare access and quality and healthy behaviours while the utilisation of Information and Communication is slightly correlated with Quality and healthy behaviours only.
 The number of health problems reported by individuals is only slightly correlated with Information and Communication Usage and it is unrelated to Services and devices utilisation. Therefore, individuals who could take more advantage of Services and devices, due to their health status, are more likely to be oriented towards information and communication usage only.

Lessons learned
The study reported here reveals the potential of ICT for Health to promote active and healthy individuals and increase empowerment. Even though our findings relate to Internet users, it is worth pointing out that new health inequalities are emerging due to the impact of the "traditional determinants of heath" on ICT readiness.
Therefore, eInclusion policies related to ICT for Health are needed to ensure that individuals with low socio-economic status and more health problems are able to benefit from these types of technologies. These ICT for Health divides specially impact on the elderly. However, there is an opportunity for them to engage with the Information Society through ICT for Health due to the importance of health issues in their daily life.
The relationship between the different typologies of ICT readiness and ICT for Health Motivation and Impact reveal that:  Young individuals are already using this type of technologies mostly in relation with wellness and healthy life style. These uses enable an entire world of possibilities related with health promotion and prevention, especially considering that young individuals are heavy Web 2.0 users.
 Middle age individuals are also active users of ICT for Health acting as gatekeepers of this type of technologies within the household. Therefore these individuals could act as enablers for others i.e. both for the elderly and the young within households.
 The elderly are basically using ICT for Health for information and communication purposes. There is a gap between this type of use and services and devices uses which could be more effective in relation with cure and chronic conditions.
Individuals between 16-54 with chronic conditions, going under long-term treatment and with more than one health problems are more likely to use ICT for Health than individuals without these types of health problems. Individuals between 55-74 who are healthy are more likely to use ICT for Health, especially for Information and Communication, than individuals with worse health status. Therefore, in the short term, this group of individuals will be pushing for health systems to provide them with new solutions (services and devices) when they need to tackle a health problem. This pressure will increase during the next decade when middle age individuals become elderly. Therefore health systems are facing the challenge of having to promote further ICT innovation to answer these new demands. While this is an opportunity to improve both sustainability and efficiency of healthcare system, it is associated with a number of challenges linked to eHealth deployment.
Further, during this transition, health systems cannot leave out the elderly who are not active and healthy: this group of individuals cannot be omitted as they are the current intensive users of healthcare systems. There is an opportunity to include them in the Information Society by improving ICT readiness and ICT for Health willingness and awareness.

Background and rationale of SIMPHS2
SIMPHS 2, the Strategic Intelligence Mapping on Personal Health Systems phase 2 (SIMPHS2), is a project carried out by the IPTS in cooperation with DG INFSO. Taking a demand side approach, SIMPHS 2 aims to further expand the fact findings from SIMPHS 1.
The conclusions drawn upon completion of SIMPHS phase 1 in May 2010 identified the following set of areas that deserve further research and analysis:  to enlarge the scope of our focus from PHS to IPHS (Integrated Personal Health/Care Services) as a result of emerging trends of convergence between health and social care also in the provision of ICT enabled services  to adopt a demand driven research design as opposed to the supply-driven one that characterised SIMPHS Phase 1;  to include a fact finding component, beyond RMT, focusing on Telecare (and its more sophisticated versions such as Ambient Assisted Living AAL, or Independent Living, IL), Mobile Health, and Wellness; and  to produce empirical and prospective analysis of potential impacts which can support the Impact Assessment for relevant INFSO policy activities (such as European Large Scale Actions (ELSAs) or European Research and Innovation Partnerships (ERIPs)), and also with the purpose of raising awareness and creating consensus among the different stakeholders through the sharing of the knowledge base.
In light of the above, DG INSFO/H1 requested JRC-IPTS to expand the scope of the research developed during SIMPHS Phase 1 to new areas of interest (Telecare, Mobile Health, and Wellness) and study the integration between disease management and RMT as well as health and social care in order to extract strategic intelligence and quantitative evidence to support the policy process. SIMPHS 2 investigates the use of Personal Health Systems (PHS), starting with the Remote Patient Monitoring and Treatment (RMT) segment for chronic disease management. The specific diseases of SIMPHS 2 focus are diabetes, Cardio Vascular Disease (CVD) and Chronic Obstructive Pulmonary Diseases (COPD). Expected results aim at supporting policy making by providing evidence on the current development and use of RMT from the perspective of the demand side (policy makers, hospitals, health care professionals and end-users) identifying drivers and barriers to its large-scale take up in Europe using three axes: diffusion of innovation, governance and health impact assessment. Thus, impact on quality of life and treatment costs will be at the core of the study. In addition, it will also look at current reimbursement systems for RMT and coordination between health and social care services for the use of these applications.
Within this background to gain more insights from the perspective of the demand supply an online panel survey to Internet users has been carrying out on 14 EU countries about Health and ICT.

From eEurope to Digital Agenda for Europe
The European Commission eHealth Action Plan defines eHealth as "the application of information and communications technologies across the whole range of functions that affect the health sector' and including 'products, systems and services that go beyond simply Internet-based applications" [1]. This definition has been expanded by the eHealth task force in support of the Lead Market Initiative [2] to encompass four categories of applications: 1. Clinical information systems (specialized tools for health professionals within care institutions, tools for primary care and/or for outside the care institutions); 2. Telemedicine and homecare systems and services; 3. Integrated regional/national health information networks and distributed electronic health record systems and associated services; 4. Secondary usage non-clinical systems (systems for health education and health promotion of patients/citizens; specialised systems for researchers and public health data collection and analysis; support systems for clinical processes not used directly by patients or health care professionals. eHealth has figured high in the European Commission Information Society policy agenda for a decade: starting with the eEurope framework, 2 continuing into i2010 strategy [6], Stated in very compact form the objective pursued by eHealth policy is to 'improve the quality of care and reduce medical costs' [7:29]. This objective summarises the various promises of eHealth that have been heralded for more than a decade (and very effectively reviewed in Lapointe [9]), which include amongst others:  Reducing medical errors, drugs adverse events and associated costs (i.e. through adverse events computerised reporting systems, ePrescription of diagnostic procedures, electronic health records, etc);  Improving adherence to prescriptions (through reminders and telemonitoring);  Reducing in-patient costs while improving health outcomes (telemonitoring);  Supporting and improving the work of professionals in various ways (Picture Archiving and Communication Systems, tele-radiology, Computerised Physicians Order Entry, online transmission of clinical tests results);  Streamlining and making the administration of hospitals more efficient (Integrated computerised systems for billing, order entry, discharging, etc.);  Increasing access and convenience for users (eBooking, access to their electronic health records, portability of their information across the system, etc.).

Healthcare and ageing in the new policy context toward 2020
Toward the end of 2009 the first report of the European Research Area Board (ERAB) placed ageing and healthcare among the grand challenges on the road toward Europe's Renaissance. 3 Ageing and health figure prominently in the new EU2020 Strategy, 4  EU2020 includes as sources of structural weaknesses in Europe, 7 the acceleration of demographic ageing and the low workforce participation of older workers and considers ageing among the longterm global challenges that the European social market model is facing. 8 In the 'smart pillar' of the strategy, ageing is among the objectives of the flagship initiative "Innovation Union" 9 (i.e. 'technologies to allow older people to live independently and be active in society' will be one of the first "European Innovation Partnerships" to be funded), whereas within the 'inclusive growth pillar' an important reference is made to the need for reducing health inequalities and for promoting active and healthy ageing, thus, contributing to social cohesion and higher productivity. 10 Last but not least, EU2020 stresses the strategic importance of leveraging the full potential of ICT in pursuing smart, sustainable and inclusive growth. 11 In sum, the new EU strategy provides full policy support, and actually calls for, the kind of two-fold approach that ICT can enable in the domain of health and social care: coping with societal challenges while creating new inclusive market opportunities.
Such an approach is further reinforced in the new Digital Agenda for Europe (see footnote 6). The Digital Agenda stresses how "by harnessing the full potential of ICT, Europe could much better address some of its most acute societal challenges: climate change and other pressures on our environment, an ageing population and rising health costs". 12 The Digital Agenda devotes also an entire paragraph to "Sustainable healthcare and ICT-based support for dignified and independent living", 13 where it underlines how the action in this area will contribute to the earlier mentioned European Innovation Partnership foreseen by EU2020 and also stresses that previously launched policy actions such as the Lead Market Initiative 14 will play a key role in further catalysing the deployment of eHealth with an explicit mention of those services and applications addressing the needs of chronic patients (telemedicine, Telemonitoring, mobile health) and of the elderly (Independent Living and Ambient Assisted Living).
As such, the contents devoted by the Digital Agenda to eHealth fully support the two-fold view of the potential of ICT in health and social care which is to both cope with societal challenges and create opportunities for innovation and economic growth. Hence, the new policy context confirms and reinforces the support to ICT enabled innovation in the domain of health and social care that were already present in the previous policy antecedents, such as the eHealth Action Plan, the Lead Market Initiative, the Ambient Assisted Leaving Joint Programme and various other communications, studies and research projects. Considering that one of the key pillar of the new Digital Agenda is the deployment and adoption of Next Generation Access [10] networks throughout Europe, ICT enabled health and social care services can be among the added-value 'contents' to be conveyed through these new fast and very fast "pipes" valorising the investments in infrastructure. As illustrated in the outer part of Figure 1 below, a virtuous cycle of the digital economy could be unleashed between increase demand for digital services, roll out of NGA networks, and creation of content and borderless services. Personalised digital health and care services could very well be among the key contributor to such a cycle. Mobile health, for instance, is one of the potential sources of spill over 5 We  15 Yet, the inner part of the figure also highlight the vicious cycle that has blocked so far the realisation of the full potential for a European digital economy and society. The main eHealth related target of the DAE (and the corresponding actions described in the scoreboard are the following (the first two are split into separate targets): Action 75a: Give Europeans secure online access to their medical health data 16 Objectives: increase empowerment and quality of life for citizens while contributing to healthcare system sustainability, contribute to EIPAHA Target: undertake pilot actions to equip Europeans with secure online access to their medical health data by 2015 Action 75a: achieve widespread telemedicine deployment 17 Objectives: increase empowerment and quality of life for citizens while contributing to healthcare system sustainability, contribute to EIPAHA Target: achieve by 2020 widespread deployment of telemedicine services Action 76: Propose a recommendation to define a minimum common set of patient data 18 Objectives: establish minimum set of criteria to achieve inter-operability of patient records for cross-border access and/or exchange. Contribute to action 77 Target: to be achieved by 2012.
Action 77: Foster EU-wide standards, interoperability testing and certification of eHealth 19 Objectives: unleash an EU eHealth market by overcoming local and market fragmentation; Target: achieve the above by 2015 through stakeholder dialogue.

European Innovation Partnership on Active and Healthy Ageing
On 7 November 2011 the Steering Group of the pilot European Innovation Partnership on Active and Healthy Aging agreed on joint actions in response to the societal challenge of an ageing population. 20 The overarching objective is to ensure that the average European citizen has two more active and healthy years to live by 2020, focusing on the three main areas of life events:  Innovative solutions to prevent falls and support early diagnosis for older people;  Co-operation to help prevent functional decline and frailty, with a particular focus on malnutrition;  Spread and promote successful innovative integrated care models for chronic diseases amongst older patients, such as through remote monitoring. Action should be taken in a number of the EU's regions;  Improve the uptake of interoperable ICT independent living solutions through global standards to help older people stay independent, mobile and active for longer.
Furthermore, the expected results would be threefold:  An improvement of the health status and quality of life of Europeans, especially older people;  An improvement of the sustainability and efficiency of health and social care systems;  Boosted EU competitiveness through an improved business environment for innovation.

Conceptual framework: towards a social determinants of ICT for Health
The roots of a social approach to health are grounded in the recognition that social and environmental factors decisively influence people's health. This approach is ancient and has received the support from WHO since 1950. 21   Socioeconomic and political context is broadly defined to include all social and political mechanisms that generate, configure and maintains social hierarchies, including: the labour market, the educational system, political institutions and other cultural and societal values.
Context, structural mechanisms and the resulting socio-economic position of individuals (the most important structural stratifiers and their proxy indicators include Income, Education, Occupation, Social Class, Gender, Race/ethnicity) taken together make up "structural determinants" and in effect it is these determinants we refer to as the "social determinants of health inequities." The underlying social determinants of health inequities operate through a set of intermediary determinants of health to shape health outcomes. The main categories of intermediary determinants of health are: material circumstances; psychosocial circumstances; behavioural and/or biological factors; and the health system itself as a social determinant.
The role of the health system becomes particularly relevant through the issue of access, which incorporates differences in exposure and vulnerability, and through intersectoral action led from within the health sector. The health system plays an important role in mediating the differential consequences of illness on people's lives.
This framework does not relate directly to ICT for Health, nevertheless the structural determinants perfectly overlap the core argument of personal and positional categories of and distribution of resources in van Dijk's "Causal and Sequential Model of Digital Technology Access by individuals in Contemporary Societies" (Figure 3).

Figure 3: A Causal and Sequential Model of Digital Technology Access by Individuals in Contemporary Societies
Source: van Dijk 2005 [12] p.24.
This framework has been summarised by van Dijk as follow:  Categorical inequalities in society produce an unequal distribution of resources.
 An unequal distribution of resources causes unequal access to digital technologies.
 Unequal access to digital technologies also depends on the characteristics of theses technologies.
 Unequal access to digital technologies brings about unequal participation in society.
 Unequal participation in society reinforces categorical inequalities and unequal distribution of resources.
However the term access goes beyond broadband connectivity and refers to four stages: These two frameworks summarised in Figure 2 and Figure 3 are the roots of our conceptual framework Towards social determinants of ICT for Health ( Figure 4):  Social determinants of health and health inequalities, therefore structural and intermediary determinants produce different levels of ICT access (motivation, material, skills and usage).
 Unequal access to ICT will generate different levels of ICT for Health access as well as different levels of willingness to use ICT for Health. o Health care quality.  These impacts could modify both structural and intermediary determinants and distribution of health and well-being.

Figure 4: Social Determinants of Health and ICT for Health conceptual framework
Source: Based on WHO [11] and van Dijk [12].

Outline of the report
This report is structured as follows:  Chapter 1 provides a brief observation of the political context and the analytical framework around the main issue tackled by this study.
 Chapter 2 contains a description of the design methodology on which the research is based. This includes information about the scope of the population being researched, the sampling strategy and the sample used as well as the description of the survey design and field work process.
 Chapter 3 refers to the socio-demographic description of the population being researched.
Beyond the sample quotas of gender and age, which are pre-defined, we obtained information about the characteristics of the individuals such as their level of education, employment situation or, type of household. Furthermore, a socio-demographics comparison between our sample and European population was carried out.
 Chapter 4 mainly refers to the general state of health of the European population surveyed and how they use health and social care services.
 Chapter 5 tackles Internet access, frequency of use and general activities carried out by individuals.
 Chapter 6 contains individuals' utilization of health information sources and perception of trust.
 Chapter 7 focuses on individuals' motivations to use ICT for Health (triggers and empowerment) as well as the barriers perceived.
 Chapter 8 refers with ICT for Health access, utilization, awareness and willingness to use these technologies in relation with Health.
 Chapter 9 provides insights on Internet health information and factors to evaluate Internet sites.
 Chapter 10 tackles individuals' perception of ICT for Health impact and behavioural change. Furthermore, this chapter analyses how individuals evaluate ICT for Health sites.
 Chapter 11 presents the results of the multivariate analysis carried out and how we move from questionnaire items to conceptual dimensions of the conceptual framework.
 Chapter 12 concludes with some lessons learned and policy recommendations.

Questionnaire design
To reach our target population, we have used the Internet as a methodological tool. As argued elsewhere survey research[13] is becoming a frequently used methodology due to the advancement of computer hardware, software and increasing access to the Internet. Furthermore, online surveys offer a valid alternative to the postal, telephone or face-to-face surveys as long as technical, methodological, ethical and legal considerations are taken into account. [14,15,16,17].
The questionnaire was designed considering our framework in Figure 4 as well as the policy context The full questionnaire and the coding manual are available in Annex 1. Questionnaire and coding manual while Annex 2. Online panel provider describes the companies which carried out the fieldwork.
The questionnaire was structured in 5 blocks:  Block E: Socio demographic profile of participants.

Survey design and sampling
It is appropriate at this point to explain the methodological design of the research. To obtain the objectives therefore, an ad-hoc research study has been designed to collect first hand information. Table 1 resumes the technical information about the study. Weighting by country to be able to interpret the overall data.

Sampling
Individuals have been sampled in a completely random manner.
The demographic groups are organised by the cross-referenced quotas of gender and age group, as follows:  Women aged between 16   Finally, having defined the object population of the study, the sample is displayed in Table 3. The sample has two essential characteristics:  Firstly, an equal size sample has been chosen for each one of the countries being studied. This leads to an equal level of reliability in the results obtained in each of the countries.
 Secondly, the choice was made to use a fully representative sample for the distribution of the target population, according to gender and age group, which means that there is no need for any weighting to be applied to interpret the data.  Table 4 shows the study sampling errors (overall and by quotas). They are calculated for a probability no greater than 95.5%, and for the least desired context, i.e. a maximum indeterminate probability (p = q = 50%), for the reference population.
The sampling error is the error caused by observing a sample instead of the whole population. The sampling error can be found by subtracting the value of a parameter from the value of a statistic and is calculated with the formula given below: Where: e = Sampling error Z= Confidence level. The value for selected alpha level of .0225 in each tail = 2. The value of Z is set to 2, representing a confidence level of 95.5%. We want the highest accuracy possible, with the smallest sample size. This confidence level gives us the best trade-off between these two goals. The expected scenario is maximum indetermination (p=q=50) where: p= the conversion rate we expect (estimate of the true conversion rate in the population) q= The conversion rate we don't expect N= Total population (GP's) n= Proposed sample (GP's) These sampling errors, in fact, determine the statistical reliability of the sample and, consequently, it is necessary to take them into consideration. The overall error margin, therefore, is + 0.85%, with a country specific error margin of +3.16%. These errors are in line with the statistical criteria that validate the sample design and, the sample being representative and reliable, it is possible to extrapolate the study results to the target population group in the selected countries. As has been previously explained, the sample distribution is proportional and representative in each country, according to the proportion of individuals that have used the Internet in the last three months by gender and age group. This means it is not necessary to weight the sample to interpret the country-specific data.
However, as each country's population is clearly different, in spite of being sampled in equal measure, weighting has been applied to ensure a representative sample for interpretation of the overall data, i.e. for all the selected countries.
In this report, we analyse the results on three levels: the average for the 14 Member States, the differences according to the socio-demographic characteristics of the respondents and issues with respect to state of health and the national average. The overall analysis and the socio-demographic and the state of health analyses are based on the 14 Member States, i.e. the average of the results for the 14 Member States. This average is weighted to reflect the actual population of each of the Member States, as was previously explained.
Each country's weighting factor has been calculated by dividing the proportion of the country's population to the total population (210,244,411) by the proportion of individuals in each country's sample (1,000) to the total sample (14,000). It is worth specifying at this point that a regional quota has been introduced in Spain to interpret the data for 3 Autonomous Regions in Spain with sufficient sample size. The Autonomous Regions are: Andalusia, Basque Country and Catalonia. Table 6shows the sample from these Autonomous Regions:  They are calculated for a probability no greater than 95.5%, and for the least desired context, i.e. a maximum indeterminate probability (p = q = 50%), for the reference population. As gender or age quotas for the different Autonomous Regions were not established from the outset, each resulting sample must be weighted to allow for the interpretation of the specific data for Andalusia, the Basque Country and Catalonia. For this purpose, the population distribution in Spain, according to gender and age quotas, was used as a benchmark. Table 8 shows the weighting coefficients: It should be noted that throughout the document, a (*) next to the data in the tables has been used to indicate statistically significant associations. These associations are positively indicated in the tables through analysis of the corrected standardised residuals. A statistically significant association is indicated in the cell when the statistical value is outside +1.96.
Finally, a brief reminder about the current research project is required. The data in the report refers to an Internet user population, which also forms part of online panels. Accordingly, it can be deduced that the respondents' profile as ICT users during the fieldwork process is more advanced than that the general population of the countries that were surveyed. In this sense, a new angle to the research project arises, which shouldn't be understated when indicating the future tendencies of the European population as a whole.

Field work process
The fieldwork period ran from 20 July 2011 to 20 August 2011. Three consecutive launches were established from the outset:  The first launch took place in the United Kingdom (20.7.11) and Spain (21.7.11), which were the countries in which the pilot study took place.
 Secondly, and after having checked that no significant incidences existed, the launch went ahead in France and Italy on 26.7.11.
 Finally, a joint launch was to take place in the remaining countries on 29.7.11. Delays occurred in Finland (launched on 1.8.11), Slovenia (3.8.11) and Slovakia (4.8.11) due to issues with the optimisation of the questionnaire translations.
The fieldwork process included a pilot study to check the validity and reliability of the research design and the questionnaire (see Annex 3. Pilot study). The pilot study passed without notable incidences. The following table shows the data collection schedule for the different countries. Source: Authors' elaboration. Table 10 summarises the interview distribution by overall data and country within the fieldwork process:  To achieve 14,000 responses, it was necessary to send 72,417 invitations to the panel, to which, 22,141 responses were received.
 8,141 of 22,141 received responses were discarded, mainly as they did not fall into the required quotas (7,556), but because they have been rejected (585). The reason for rejecting a response was incompleteness and/or poor consistency of responses. The following graphs show the gross and net response rates respectively. Figure 5 shows the gross response rate. This corresponds to the proportion of received responses to the total number of invites. It can be observed that the average gross rate for all the countries is 30.6%, with relatively homogenous results, reaching a very high rate -59.2% -in Germany.

Figure 5: Gross response rates
Source: Authors' elaboration. Figure 6 shows the net response rate. This is obtained from the quotient between the validated interviews (1,000 per country, 14,000 in total) and the total number of invitations sent out (in each country and overall). The net response rate analysis excluded responses for over quota samples, and rejected interviews.  Lastly, the average interview length was 23.2 minutes, with considerably homogenous results per country, varying between 20.5 minutes in the UK to almost 28 minutes in Estonia. Figure 7 summarises the interview length data per country:

Data analysis
Statistical analyses were performed using SPSS version 19.0 following three steps.
Firstly, descriptive statistical analysis was undertaken. This analysis includes frequencies of all items and cross tabulation with socio-demographics and health status. To attribute statistical significance to the differences obtained an associated Chi-square test was carried out.
Secondly, following our conceptual framework, in order to confirm the several internal complementarities of grouped items, the means and their significant correlation were checked. Then, factor analysis was used to assess item correlations and identify common relationships between similar items, allowing the items to be categorized into various themes or factors (dimensions). An analysis of the correlation matrix (KMO and Bartlett's test of sphericity) was carried out to check that the correlation matrixes were factorable. Data reductions were undertaken by principal components analysis using the Varimax option to identify possible underlying Thirdly, ANOVA test and correlations were carried out to identify the relationship among the dimensions previously identified and to characterise different typologies of users, behaviours, motivations. To attribute statistical significance to the differences obtained associated tests were carried out.

Gender
Now that the sample characteristics of the citizens taken from the 14 European countries forming part of the research have been discussed in detail, we will now approach the explanation of their socio-demographic characteristics.
The sample of the European citizens being researched is split nearly evenly by gender, with slightly more women taking part (51.5%). No significant differences are observed by country in terms of the sample distribution by gender. It is only worth mentioning the relatively higher number of men in Italy (54.4%) and women in Estonia (53.6%).

Age
As for the age structure of the sample, some relevant differences are observed here. Almost twothirds of the total number of persons sampled (62.2%) fall within the middle age group (between 25 and 54 years old). Additionally, young citizens (between 16 and 24 years old) make up 19.8% of the sample, with 18% of the sample consisting of older citizens (between 55 and 74 years old). Base: Whole sample.
On a per-country basis, there are relatively more young citizens in the samples for Estonia (24.0%) and Slovakia (23.5%). It is also worth highlighting the presence of respondents from an older population (between 55 and 74 years old) in the Scandinavian countries: 23.8% in Denmark, 23.0% in Finland, and 24.5% in Sweden. Base: Whole sample.

Country of citizenship
Virtually all the sampled European population are citizens of their country (95%), a percentage that rises to 98% for EU citizens. Therefore, only 2% of the sample relates to non-EU member state nationals.

Country of birth
As with nationality, the large majority of the participating citizens are native to the country (93%) or born in EU countries (96%). Therefore, only 4% of the sample was born outside of the EU. Base: Whole sample.

Level of education
With respect to the level of education, around half of the sampled European population (46%) attained the secondary education level, slightly more than the 38.8% of citizens who attained university level education. 15% of the sampled population attained the primary or lower secondary education level. On a per-country basis, the following scenarios can be highlighted, considering that the sample is composed of Internet users which means that the lower the diffusion of the Internet in a given country, the higher the education level among respondents in that country  Belgium (55.6%), Spain (53.7%), France (45%), Sweden (42%) and the United Kingdom (44%) stand out in terms of participating citizens with a university education;  Austria (29%), Denmark (45%) and Finland (46%) stand out in terms of a greater relative presence of lower education levels, much higher than in their general population.

Figure 15: Level of education completed (E5) by country
Base: Whole sample.

Labour position
With respect to entry into the workplace, more than half of the sampled population (58%) were employed or self-employed, 10% unemployed, 14% were students and 18% were not part of the labour force for different motives. Base: Whole sample.
On a per-country basis, the high employment ratios in Estonia (73%), France (63%) and Sweden (62%) stand out. On the other hand, and in tune with the data for the country as a whole, 20% of the people sampled in Spain are unemployed. By job category, office clerks (19%), customer services clerks (10%), personal and social services (7%), associate professionals (6%) and small enterprise managers (6%) stand out.

Type of location
With respect to the urban density of the sampled population, the following distribution is worth indicating: 39% live in densely populated areas, 39% in intermediate size cities, and 22% in thinly populated areas. Base: Whole sample.

Figure 19: Type of locality (E9) by country
Base: Whole sample.

Members in the household
Around a third of the sampled population (31%) live in 2-member households, and 32% live in a household with 4 or more members. 16% of the citizens sampled live in single-parent households, and 22% in households with 3 members.

Figure 20: Members in the household (E19)
Base: Whole sample.
On a per-country basis, there are households with many members in Estonia (39%), Spain (45%), Italy (45%), Slovakia (50%) and Slovenia (47%). In turn, the Scandinavian countries, particularly Denmark and Finland, fewer member households are more prevalent than the sample average. Base: Whole sample.

Socio-demographic comparison: Internet users (sample) and population
To be fully transparent a comparison of socio-demographic characteristics between our sample of Internet users and population has been carried out. As it was expected Internet users are more likely than the general population of 14 EU countries surveyed to be younger, have higher levels of education; and be employed. The same comparison has been also carried out by country. It is worth pointing out that the differences are even more accentuated: the lowest the level of Internet use, the highest the differences.

Health status
Overall, the European population is in a favourable state of health. Around three-quarters of the sample (74%) state they are in a good state of health, 18% state that it is neither good nor bad, and 7% of the sample population state that they are in a poor state of health. Base: Whole sample.
Poor state of health is associated with the older population (11%); the population with lower education levels (10.7%); the unemployed (9.5%) and inactive (17%); the population living in thinly populated areas (8.3%); single parent households (12%); and long-standing patients (17%). On the other hand, a positive state of health is related to men (76%); young people (88%); a university education (78%); entrepreneurs and the self-employed (78%), students (87%); the population living in densely populated areas (75%); households with several members; and the absence of longstanding illness (92%). Among those countries sampled, Spain (82%), France (81%) and Slovakia (82%) stand out as having good states of health, whereas in Germany (11%), Denmark (12%) and Holland (10%), the worst states of health are clearly seen to be above the sample average. However, more than half of the sampled population (56%) stated that they have (or have had) a long-standing illness or health problem. Base: Whole sample.
Through an analysis of descriptive statistics, it is possible to link the long-standing illnesses or health problems to women (42% of the total); the older population (62% of citizens aged 55 to 74 years old); the lower level of education; unemployment (44%) and inactivity (64%); the poor state of health (92%); and households with few members. On the other hand, the absence of a longstanding illness or health problems are associated with men (58%), the young (71%), a university education (60%), self-employment and entrepreneurs (60%), a good state of health overall (70%), and larger households. On a per-country basis, the existence of long-standing illness and health problems is more frequent in Germany (48%), Denmark (45%) and Finland (45%), whilst the absence of long-standing illness and health problems is more prevalent in Belgium (63%), France (65%), Italy (61%) and Slovakia (59%). It is also worth highlighting that 65% of the sampled population state that they have undergone a long-term medical treatment. Base: Whole sample.
Again, women, the older population, lower education levels, the inactive, those residing in thinly populated areas, households with few members, a poor state of health and the existence of longstanding illnesses are statistically linked with long term medical treatments. Germany (40% of the total), Spain (34%), Sweden (36%) and the United Kingdom (35%) stand out for having a greater relative population on long-term medical treatments.

Figure 27: Long-term medical treatment (A6) by country
Base: Whole sample.
In the same way, 36% of the sampled population state that their regular life has been severely restricted due to a health problem. This severe restriction to normal life as a result of a health problem is linked with the older population, lower education levels, unemployment and inactivity, thinly populated areas, households with few members, a poor state of health and the presence of long-standing illnesses. The countries with the greatest limitations on normal life as a result of health problems are Austria (42%), Germany (46%) and Estonia (45%).

Figure 29: Limited in activities people normally do due to a health problem (A7) by country
Base: Whole sample.
In general, these health problems are statistically linked with the female population, the older population, low education levels, unemployment and inactivity, poor states of health and longstanding illnesses. On a per-country basis and main health issues, the high percentages of allergies in Finland and Sweden stand out (43% and 40% of the total respectively), migraines and headaches in Italy (40%), and chronic anxiety and depression in Spain (25%). Base: Whole sample.

Informal carers
With respect to long-standing illnesses or health disabilities, more than half, specifically 55% of the sampled European population indicate that someone close to them has these problems.

Figure 31: Someone close to you currently experience long-term illness of disability (A9)
Base: Whole sample.
The closeness of long-standing illnesses or health disabilities is associated with women, young people, students, densely populated areas and large households.  In the same way, around a third of the sampled European population (32%) take care of someone experience long-term illness or disability. Base: A10 = Yes -49% of whole sample.
The characterisation of those persons who take care of others, show us that this dependence situation is linked with the older population (38% of citizens between 55 and 74 years old care for another person) and inactivity (36%). Base: A10 = Yes, 49% of whole sample.
On a per-country basis, caring for a person stands out strongly in Estonia (52% of the total) and Italy (68%).

Figure 34: Taking care of a person experience long-term illness or disability (A10) by country
Base: A10 = Yes 49% of whole sample

Health and social care demand
On average, the sampled population has been seen by a doctor 5.2 times during the previous twelve months, a doctor or nurse has provided home care, 0.65 times; and a social worker, 0.48 times. Base: Whole sample.
With respect to the sample populations' socio-demographic characteristics, it is worth mentioning the higher levels of medical care received by women (5.9 visits to the doctor during the last twelve months); the older population (6.12); the less educated population (5.6 visits among citizens with primary education); the inactive population (7.29); the densely populated areas (5.26); the citizens in a poor state of health (13.9 visits to the doctor by the section of the population in poor health); and the citizens with long-standing illnesses (7.89).
On a per-country basis, the higher levels of medical care in Denmark (around an average of 2 visits to the doctor in the last twelve months), Holland (1.45), Belgium (an average of 2.7 home medical visits) and France (1.71) stand out. Conversely, the lower levels of care occur in Estonia, Slovenia and Slovakia. Base: Whole sample.

Quality of care
With respect to the specific uses of medical services undertaken by doctors or nurses on the sample population, it is worth indicating that:  61% of participants state that they always or very frequently have the results of medical exams explained to them;  52% state that they always or very frequently have the different treatment options explained to them by the healthcare professionals; and  54% state that the healthcare professionals always or very frequently listen to their opinions and take their preferences into account. These favourable opinions about the relationship between the healthcare professional and the patients are statistically linked by some of patient's socio-demographic characteristics. In particular, being older, having a university education, being in self-employed or an entrepreneur, from the more densely populated areas, in poor state of health and having a long-standing illness. On a per-country basis, the perception of service quality with respect to the patient-healthcare professional relationship is strongly evident in Belgium, Denmark, Spain and France.   Individuals were also questioned on how often they ask their usual source of care (doctor or nurse) about their results of medical exams; the different treatment options and to consider their opinions.
 59%% of participants state that they always or very frequently asked have about the results of medical exams;  52% state that they always or very frequently asked about the different treatment options; and  50% state they always or very frequently asked health professional to consider their opinions These favourable opinions about the relationship between the healthcare professional and the patients are statistically linked by some of patient's socio-demographic characteristics. In particular, being middle age, having a university education, being in a poor state of health and having a longstanding illness. Base: Whole sample.

Internet access and frequency of use
The use of the Internet and Information and Communication Technologies (ICT) are key for the advancement of the new uses in healthcare. This study also provides relevant information in this aspect. 93% of the surveyed population uses the Internet at home at least once a day, 42% do so at work, and 14% at least once a day in other locations.

Figure 44: Internet access and use (C1)
In terms of socio-demographic characteristics, the intensive uses of ICTs are statistically linked with men (64.4% of men use the Internet at least once a day at work), the youngest age group (70.7% of the sample population between 16 and 24 years old connects to the Internet away from the home and at work), a university education (73.2% of the participants with a university education use the Internet at work at least once a day), the student population and the population density. On a per-country basis and looking at Internet use, it is worth indicating the intensity of use whilst at work in Estonia (62%), Sweden (56%) and Slovenia (55%).  Base: Whole sample.  Never  43  51  39  43  27  33  32  49  40  57  40  38  33  50  Less than  once a  month   22  19  23  20  26  19  31  18  14  13  24  22  23  21 At least once a month (but not every week) Base: Whole sample.

Internet-related activities
With respect to Internet based activities, the sampled population mainly uses it to search for information (67.6% every day), sending e-mails with attachments (40.6%), online banking (20.3%), social networks (38.6%) and instant messaging (22.8%). As with the general situation, the main uses of the Internet are linked with the male gender, the youngest age groups, a university education, self-employment and entrepreneurs, studying, population density and a good state of health.
To be fully transparent a comparison between Internet activities performed by individuals in our sample and Internet activities reported by a representative sample of EU27 population was carried out (see Annex 4. Internet activities comparison). The results of this comparison reveals that our sample is composed by slightly advance Internet users: the less the diffusion of the Internet by country the higher the differences.  Base: Whole sample.

HEALTH INFORMATION SOURCES AND TRUST
Despite the importance of the Internet as an empowering tool for health, and with respect to the set of available information sources, the surveyed citizens continue to consider direct interaction with doctors (75%) and nurses (40%) to be most relevant. In turn, the growth of the Internet as a channel for health interaction stands out, if it is taken into account that its relevance (35%) is already greater than that of pharmacies (32%). Base: Whole sample.
The perceived importance of the Internet as a main channel for health interaction is linked with women (81%), the middle population set (81% of people aged between 25 and 54 years old), the worst states of health, and the existence of long-standing illness (82%). Estonia (87%), Slovakia (94%), Slovenia (93%) and the United Kingdom (89%) lead the Internet as source of health information. Medical and health institutions continue to lead in terms of perceived trust with respect to the health information available to European citizens. 26% of participants fully trust medical and health institutions, with 55% trusting them somewhat. Something similar, although not as marked, occurs with the national health authorities. When it comes to online companies, the percentage of trust is very much lower. 4% of the European population trusts them fully, whilst a third trust them somewhat. Base: Whole sample.
The perceived importance of the Internet as a main channel for health interaction is linked with women (81.3%), the middle population set (80.7% of people aged between 25 and 54 years old), the worst states of health, and the existence of long-standing illness (81.8%). On a per-country basis, trust in Internet-based health is led by Denmark (43% of all participants), Italy (48%), Holland (41%) and the United Kingdom (40%).

Triggers
Beyond specific uses of ICTs in the health sector, the research has also captured the thoughts of European citizens with respect to facilitators and barriers. With respect to the factors that motivate the use of ICTs in health, more than a third of the sampled European population indicates a significant use of ICTs in health to better understand a health problem or disease (39.2%), to find additional sources of information (36.1%) and to develop knowledge and personal satisfaction (34.7%). A little further behind, but still with a relevant frequency, there is the perception that ICTs in health are very useful to help a family member or a friend who is ill (30.7%), to prevent illnesses or to adopt a more healthy lifestyle (28.4%), to find a solution to or a treatment for a health problem (27.5%), to obtain different points of view about an issue (22.3%), and to access an online health service (20.9%). Finally, and as a counterpoint, only 10.6% of European citizens give much importance to the use of ICTs in health for participating in online discussions. With respect to the socio-demographic characteristics of the population, the perception of the importance of ICTs in health for the health or wellness sector is much more positive for women, young people, the middle aged, those with a tertiary education, the employed, students, and people in a bad state of health or with long standing illnesses. On a per-country basis, the greatest perceptions of the relevance of ICTs for health use are found in Slovakia, Slovenia and the United Kingdom. Base: Whole sample.

Empowerment
When it comes to attitudes towards health and health information sources, the research also provides empirical evidence in the case of the sample of European citizens. Overall, the sampled European citizens show they agree that ICTs, especially the Internet, improve their capacity for information and empower them with respect to their state of health. Around two thirds of the sampled citizens show they agree with the fact that the Internet improves their capacity for information and their relationships with other people. In the same manner, they consider that the Internet improves the understanding of the state of health, allows them to be more informed and to have a more proactive role in their relationship with the healthcare professionals, and gives them greater access to expert knowledge through interaction with more people. Overall, this greater digital empowerment for the European citizens when it comes to their health and the healthcare professionals is linked with higher education levels, the worst states of health and the existence of long-standing illnesses. Base: Whole sample.
On a per-country basis, this perception of greater empowerment with respect to health occurs in countries where the digital divide among citizens is more marked, particularly in Estonia, Slovenia and Slovakia. Base: Whole sample.
In the same way, the majority of the surveyed citizens consider that the Internet makes them better equipped for consultations and to relate with the healthcare professionals (64% and 62% respectively), it empowers them to make decisions with respect to their treatments and solutions (63%), and it makes them more confident in their health related exchanges with other people (62%). Similarly, the Internet also appears to be an excellent tool for health decision making, independently of healthcare professionals or the conventional health system (alternative medicine).

Figure 50: Empowerment and ICT for Health (B2)
Base: Whole sample.
Again, education levels, the state of health and the persistence of long-standing illnesses, like in countries with a greater digital divide, appear linked with this greater perception of empowerment with respect to health.  Base: Whole sample.

Figure 51: Empowerment and ICT for Health (B3)
Base: Whole sample.  Base: Whole sample.

Barriers
Just as there are factors that justify a good evaluation of health websites, the lack of privacy (51.9%), security (50.5%), reliability (47,2%) and trust (45.7%) were the four main barriers for ICT uses for health indicated by the sampled European population to be very important. Other justifications were the lack of liability (38.2%), health literacy (36.2%), knowledge (33.4%), access to ICTs for health (28.9%), motivation and interest (27.9%), and the lack of digital skills (24.4%).
With respect to the socio-demographic structure of the sampled European population, the analysis of the barriers provides significant indications. Firstly, that women are much more sensitive to the barriers to the ICT use for health than men, particularly in terms of a lack of trust (87.2%), privacy (87.9%), security (87.9%) and liability (88.6%). Similarly, the demonstration of barriers to ICT use for health is also much more evident in older people, those with lower levels of education and the inactive. Lastly, it is also worth highlighting that the presence of long standing illnesses is also very sensitive to the barriers to ICT use, particularly the lack of trust (85.6%), privacy (86.8%), security (87.5%) and liability (87.5%). On a per-country basis, from those sampled, the highest percentages are observed for Estonia, Spain, Italy, Slovenia and Slovakia with respect to the proposed indicators in assessing the barriers to ICT uses for health.

ICT for Health utilisation
When it comes to specifically using the Internet for health and wellness, the research has provided interesting information, with notable relative differences. The main use of the Internet for health is for individual information searches, rather than sharing information, communicating or interacting about health. Information searches about physical illnesses or conditions (40% of the sampled European citizens use the Internet this way at least once a month, and 25% of the citizens at least once a month, but not every week); information searches about wellness and lifestyles (33% less than once a month, and 25% at least once a month, but not every week); bookmarking a health website as a favourite to pay regular visits (20% less than once a month, and 13% at least once a month, but not every week); to look which company or organisation provided the advice or information that appears on a health website (24% less than once a month, and 14% less than once a month, but not every week); and to look for information about a mental health issue like depression or anxiety (23% less than once a month, and 12% less than once a month, but not every week). In fact, individual searches for health information using the Internet make up one of the most frequently mentioned uses by the sampled European citizens. 13% of the respondents look for information about physical illnesses or conditions; 14% look for information about wellness and lifestyles; 13% bookmark a health website as a favourite in their browser to pay regular visits; 14% look which company or organisation provided the advice or information that appears on a health website; and 12% look for information about a mental health issue like depression or anxiety.
Over half of the sampled European citizens have never used the Internet to buy medicine or vitamins online (56% of the total); participated in online support groups for people with the same health issue (60%), used social networking sites for health and wellness issues (58%); used e-mail or websites to communicate with a doctor or their office (58%); analysed the privacy policy for personal information in medical websites (52%); explained a medical issue online in order to make contact with an e-health medical service (61%) or with other users (58%); disclosed medical information on social networking sites (67%); or disclosed medical information on websites to share pictures, videos, or movies (67%). Base: Whole sample.
The following observations are notable in terms of the socio-demographic characteristics of the sampled European population. With respect to gender, and establishing significant statistical differences, women stand out for carrying out individual information searches more often. 85% look for information about physical illnesses or conditions, and 79% look for information about wellness or lifestyles. Men, on the other hand, are characterised by a deeper and more interactive use of the Internet for health. 48% of the men sampled bookmarked health websites as favourites in their browser to visit them regularly. 24% of the men sampled disclose medical information on social networking sites, and 23% of the men sampled disclose medical information on health websites using pictures, videos or movies. With respect to the remaining socio-demographic factors, the analysis shows homogeneity in terms of the overall use of the Internet for health, which is more frequent in the young population, those with a tertiary education, students and the employed, those in densely populated urban areas, people in a bad state of health and those with long standing illnesses.
.  On a per-country basis, Slovenia, Slovakia and the United Kingdom stands out due to a more intensive use of the available online health practices, in particular information searches about physical illness or conditions, about wellness or quality of life, and particularly, e-commerce in health. On the other hand, there are some specific ICTs for health uses that are used more, although the majority are not used either. 16.0% of the sampled European population has made, cancelled or changed an appointment with their family doctor, specialist or any other health professional at least once a month, which becomes 6.5% when the frequency becomes once a month, but not every week. In the same manner, around 20% of the sampled population has sent or received an email from a doctor, nurse and health organisation at least once a month, or at least once a month, but not every week. Along the same lines, around a fifth of the sampled population (16.5% less than once a month, and 9.2% at least once a month, but not every week) have received an email message about a health promotion or health prevention. The research results conclude, therefore, a quite basic usage of ICTs in health, which are centred on appointments with professionals, and the sending/receiving of emails with health professionals or health promotions/prevention. Base: Whole sample.
With respect to the socio-demographic categories of the sampled population, the following results stand out. Firstly, in clear contrast to what occurs with information searches, and unlike men, women do not stand out for their use of ICTs in the health sector. ICTs for health use are mainly used by men. Secondly, it is also worth highlighting that uses of ICTs in health are different in the youngest population compared to older age groups. Thirdly, a higher education level is associated with more intensive uses of ICTs in health. Around a third of the sampled population that have completed tertiary education have made, cancelled or changed an appointment with a healthcare professional, have sent or received an email from a health professional or organization, or have received an online message about a health promotion or health prevention. Fourthly, students and those living in densely populated areas also stand out for one of the most frequent uses of ICTs in health with respect to other labor situations or types of urban living. And fifthly, and in general terms, a good state of health and a lack of long standing illnesses is linked with the most intensive use of ICTs in health.  On a per-country basis, the greater intensity of use of the majority of ICTs for health is clearly evident in Italy, which leads the way for online consultations through videoconferencing with health professionals, accessing and obtaining medical information through an Internet provider, the use of consoles or games related to health or wellness, the use of health applications on mobile telephones, and for having received online health promotions or health preventions. Furthermore, the high level of appointments made, changed or cancelled at health centres in Spain also has to be highlighted (53.9%), or the sending or receiving of emails by health professionals and organizations in Denmark (50.7%).

ICT for Health willingness and awareness
Individuals who stated they never carry out these activities or they were not aware of them were asked about their willingness to carry out these activities.  Access or upload your medical information or health record through Internet application provided by your healthcare organization 28 14 Use a game console to play games related with your health or your wellness 12 20 Use a health/wellness application on your mobile phone 14 16 Use devices (as pulse meter, glucose meter…) to transmit vital signs or other clinical information and/or received alarms or follow-up about your health anytime, anywhere

19
Receive any message about health promotion and/or health prevention 28 34

Internet health information utilisation
When it comes to the nature of the health or wellness information that is being searched online, it is important to indicate that the large majority of the sampled European population (84.5%) looks for information for their own use. Information searches for other people, such as parents (39.1%), children (29.1%), other relatives (39.4%) and people other than relatives (39.4%) fall very short of information searches for personal use. With respect to the socio-demographic categories of the surveyed population, the individual or collective nature of the health information searches leads to some significant conclusions. Firstly, that woman are characterized by their greater usage of the Internet for health than men, both in terms of individual information (87%), and particularly, when it comes to information for other people (32% for children and 42% for parents). Secondly, to highlight that the youngest population tends to look for information for themselves (86% for the population aged between 16 and 24 years old) or for their parents (43%), whilst the oldest population is characterized by information searching for their children (36% of the 25 to 54 years old sample) or for their partners (42% of the 55 and 74 years old sample). Thirdly, greater uses of the Internet for health can be seen, both for personal use and for that of other people, in larger households. Finally, with respect to state of health, two arguments are evident. Firstly, the population in a bad state of health tends to look for information for personal use (95%). Secondly, the sampled population with long standing illnesses combines their use mainly for personal information (91%) with the use to find information for other people, in particular their partner (42%) and people other than relatives (37%). On a per-country basis, intense use of the Internet for health can be seen, both from an individual perspective and for other people, in Estonia, Slovakia and Slovenia, whilst Finland stands out in terms of information for personal use and for children, the United Kingdom for information for personal use, and Spain and Italy for information for parents and other relatives. When it comes to motives for using the Internet for health for personal use or for others, it is important to indicate two basic conclusions. The first is that the use of online personal health information is directly associated with visiting the doctor. 51% of the sampled European citizens consulted the Internet for personal health information before visiting the doctor, and 51% of the sampled European citizens consulted the Internet for personal health information after visiting the doctor. The second is that the use of online health information for other people is mainly related to a visit to the doctor that has already taken place (46%) or is unrelated to visiting the doctor (44%).

Figure 54: Internet health information and doctor's consultation (D3)
Base: Looked for information about a physical illness or about wellness or lifestyle (88% of whole sample).

Figure 55: Internet health information and doctor's consultation (D4)
Base: Looked for information about a physical illness or about wellness or lifestyle (88% of whole sample).
With respect to the socio-demographic characteristics of the sampled European population, the motives for the use of the personal online health information are linked with visiting the doctor and are carried out differentially by women, young people, those with a tertiary education, students, those in densely populated areas, and households with many members. When it comes to state of health, 69% of the sampled population in a bad state of health uses online information for personal use after visiting the doctor. In the same manner, 60% of the sampled population with a longstanding illness use online information for personal use after visiting the doctor. On a per-country basis, Estonia, Finland, Slovakia and Slovenia again stand out for the medical visit motive for their personal and collective uses of online health information. Spain can be mentioned as a stand out case, leading the way in terms of use of e-health information for personal use and for other people, after visiting the doctor (59% and 61%, respectively), as can the cases of Slovakia and Slovenia, where a quarter of the population that makes personal use of online health information, doing so independently of the medical visit. With respect to the use of health information and the Internet for other people, the analysis of statistical differences again suggests intensive use linked with a medical visit by women, young people, households with many members, and a population that is in a bad state of health or has long-standing illnesses. As a differentiating factor, the use of online medical information for nonpersonal use, which is not linked to a medical visit, is evident in the older population (50.9% of people between 55 and 74 years old), the inactive (49.8%) and single member households (55.1%).  With respect to the usefulness of the health information obtained online, around two-thirds (65%) of the sampled European population consider it to be somewhat useful. Furthermore, an additional fifth part of the sample (20%) considers it to be very useful. With respect to the socio-demographic characteristics of the population, the perception of the usefulness of the online health information stands out in the employed (66.0%) and students (67.0%), in the same manner that the information is perceived to have a greater usefulness for the population with secondary education (20.9%), the unemployed (22.0%), households with many members (21.5%) and people with long standing illnesses (22,5%). As a negative counterpoint, 5.0% of the 55 to 74 year old population who consulted online health information do not find it useful. Base: Looked for information about a physical illness or about wellness or lifestyle (88% of whole sample).

Figure 57: How useful was the health information you got online? (D5) by country
Base: Looked for information about a physical illness or about wellness or lifestyle (88% of whole sample).
Another way of discovering the usefulness of online medical information is that it can lead to users gaining new knowledge. Relevant information of this type has also been obtained from the research. Three-quarters of the sampled European population indicate that they have found online medical information to be useful for learning something. This learning is characterized by young people (78.5%), the middle age group (76.3% aged between 25 and 54 years old), those with a tertiary education (76.8%), students (78.3%), and households with more members. On the other hand, the inability to learn through the use of online medical information is characterized by older people (25.2% of the population aged between 55 and 74 years old), those with primary or lower secondary education (22.5%), the inactive (21.9%), those that live in thinly populated areas (20.6%) and households with few members (10.7% in single member households). On a per-country basis, learning through online medical information stands out in Spain (82.6%), Italy (82%), Slovakia (85%) and Slovenia (91%). The capacity for user interaction with online health information is also an element of this research. In this respect, a little under half of the sampled European citizens (46.8%) had spoken with a doctor or a nurse about information obtained online. Among those that stand out having interacted with health professionals after consulting online medical information are people aged between 25 and 54 years old (48.0%), those with a tertiary education (49.2%), the employed (48.3%) the inactive (47.8%), those from 3 member households (48.6%) and people with long standing illnesses (54,8%). On the other hand, non-interaction with health professionals after consulting for online health information is characterized by people having attained low levels of education (51.8%), the unemployed (48.7%) and students (49.5%), and those without long standing illnesses (52.0%). Base: Looked for information about a physical illness or about wellness or lifestyle (88% of whole sample).
On a per-country basis, interaction with professionals with respect to the use of online medical information stands out in Belgium (49.5%), Spain (48.9%), Slovenia (53.0%) and, above all, in Italy (60.5%). Information has also been obtained about whether getting online health information had changed individual decisions about treatments or the way citizens care for themselves. 44.2% of the sampled European population stated that the use of the online medical information affected their decisions about health treatments or the way they take care of themselves. The changing of health decisions as a consequence of online medical information is characterized by the young (48.9% of the sampled citizens aged between 16 and 24 years old have changed their health decisions as a result of using e-health information), students (49.9%), those living in densely populated areas (46.7%), households with many members, and people with long standing illnesses (47.3%). With respect to the characteristics of the people that have not changed their health decisions as a result of consulting online medical information, the following stand out: the older population (64.3% of citizens aged between 55 and 74 years old), those with lower education levels (58.8%), the inactive (60.7%), those residing in thinly populated areas (60.1%), households with few members and without long standing illnesses (58.2%). On a per-country basis, and as is now becoming the norm, Estonia (57.6%), Finland (52.2%), Slovakia (68.4%) and Slovenia (68.2%) stand out for changing their health decisions due to the use of online medical information. Lastly, information has also been collected on whether the use of online health information affects the way the sampled citizens eat or exercise. A little over a third of the European population (37.2%) states that to be the case. Again, the young population (41.2% of the population aged between 16 and 24 years old), those with a tertiary education (40.2%), students (41.2%), and residents of densely populated areas (40.9%) lead the way with respect to changing eating and exercise habits due to the use of online health information. On the other hand, a lack of change of eating and exercise habits due to the use of online information is characterised by the older population (60.6%), the inactive (61.7%), those residing in thinly populated areas (61.7%) and households with few members (58,0%). On a per-country basis, the change of eating and exercise habits due to e-health information is more effective in Spain (50.3%), Finland (51.2%), Slovakia (53.9%) and Slovenia (58.3%).

Factors for the evaluation of an Internet health site
The research has also captured the motives considered to be important by the sampled European citizens when it comes to evaluating a health website. 70.2% of the sampled population considers it to be very important that personal information is securely handled, 63.0% that the information is provided in the user's own language, 62.4% that the information should be updated, and 54.1% that health professionals should be involved online. Some distance behind, the population places a high level of importance on the fact that the website clearly states who is responsible for it (39.7%), that there are health organisations involved (36,1%), that there is interactivity (22,4%) and that governments are involved (18.4%). With respect to the socio-demographic characteristics of the population, women stand out for awarding much more relevance to the defined factors for evaluating a health website (over 90% of women consider personal information, language adaptation and updating as very important). Men only stand out for their preference for government involvement (55.2%). The middle age groups, higher levels of education, population density, and the presence of long standing illnesses are associated with the defined indicators when it comes to assessing the effectiveness of a health website.
On a per-country basis, and as in the previous case, Slovakia, Slovenia and the United Kingdom stand out from other countries in the sample in the majority of the defined indicators when assessing the perceived importance of health websites.

ICT FOR PARTICIPATORY HEALTH
The research has also obtained and assessed information about the attitudes of citizens with respect to health information on the Internet. Specifically, the sampled population was asked what action came out of looking for information about health or illnesses on the Internet. 57.6% of the sample indicated that the health information obtained from the Internet was used to propose suggestions or queries about diagnosis or treatment to the family doctor. 56.6% indicated that they had an increased feeling of reassurance and relief. 54.3% suggested that their willingness to change diet or lifestyle habits improved. 46.7% suggested that they have used online medical information to make, cancel or change an appointment with the family doctor.
Some distance behind, 29.1% of the sampled citizens confirmed that the use of medical information for health improved their feelings of anxiety; and 17.7% of citizens have changed their use of medicine without consulting with their family doctor. As is becoming the norm, women are seen to be much more sensitive to changes in attitude as a result of the use of medical information on the Internet, particularly in the proposal of suggestions or queries to the family doctor (60.5%) and in increased feelings of reassurance and relief. Men, however, are more predisposed than women to changing the use of medicine without consulting the doctor as a result of medical information from the Internet (19.0%).
The change in attitudes derived from the use of medical information for health on the Internet is more intense in the youngest population, those with a tertiary education, and those that live in densely populated areas. Lastly, and with respect to state of health and the presence of long standing illnesses, the use of medical information for health from the Internet improves the feeling of anxiety of the population in a bad state of health (32.5%); increases the feeling of reassurance and relief (58.9%) and the willingness to change diet and lifestyle habits (57.0%) in the population with long standing illnesses. Base: Whole sample.
On a per-country basis, Estonia, Slovakia and Slovenia lead the way in terms of highest frequency of attitude change with respect to the use of medical information for health. With respect to changes in diet and lifestyles, and the proposal of suggestions and queries to the family doctor as a result of the use of online medical information for health also stands out in Spain and Holland. Lastly, the population from Austria and Germany are among the most willing to change medicine without consulting the family doctor, as a result of using medical information for health from the Internet. Lastly, the research has also obtained evidence about the beliefs of the European citizens with respect to the use of ICTs for health. It has to be said that the perceptions are positive overall. 58.3% of the sampled European population state they agree that ICT use for health allows for savings in the cost of travel and time. 55.9% state that they would be willing to share personal health information with the doctor despite the privacy issue. 55.0% state that ICTs for health can improve the possibilities for caring for themselves and monitoring their state of health. 54.5% state they agree with the fact that ICT use for health leads to greater patient satisfaction. 53.5% state they agree that e-health can improve the quality of the medical services received. 50.3% of the European citizens consider that ICT use for health can change their behaviour towards a healthy lifestyle.
Slightly under half of the sample of European citizens, 43.0%, agrees that ICT use for health can improve their state of health. 41.8% consider that they would feel more comfortable and safe if they used a remote monitoring system for their health condition. 41.7% consider that ICT use for health increases ICT use in other fields of daily life. 32.2% agree that the use of health services through the Internet substitutes face-to-face consultations with doctors. 31.6% agree that online health services and face-to-face services are of equal quality. And lastly, 22.8% of European citizens agree that they would be willing to pay for access to Internet health services to improve their state of health or that of their relatives. With respect to socio-demographic characteristics of the population, women are in greater agreement than men that ICT use for health complements face-to-face use (52.7%) and that they are willing to share information with the doctor online despite privacy issues (58.1%). On the other hand, men differ from women on considering ICT use for health improves their state of health (43.2%), they advocate digital monitoring systems for their health condition (42.1%), and are willing to pay to access Internet health systems (22.5%). Positive attitudes towards ICT uses for health are also characterised in the youngest population, those with a tertiary education, and those that live in densely populated areas. With respect to bad states of health, the only notable difference from a good state of health is that ICT use for health can improve the quality of health services received (56.6%). Meanwhile, citizens with long standing illnesses clearly state their favourable perceptions of ICT use for health, with respect to citizens that don't have long standing illnesses. In particular, they state that ICT use can improve patient satisfaction (55.5%), improve caring and health condition monitoring skills (57.4%), save travelling costs and time (59.9%), and that they are willing to share personal information through the Internet with doctors and health organisations despite privacy issues (60,1%).  On a per-country basis, clear data is obtained. Estonia, Spain, Slovakia and Slovenia clearly lead from the European countries with respect to the frequency of positive perceptions of the use of the Internet for health.

ICT access dimensions
Following data analysis strategy defined in the Methodology section 2.4 a factor analysis was used to assess 14 Internet-related activities (see Section 5.2) correlations 23 and identify common relationships between similar items, allowing the items to be categorized into various dimensions.

Triggers dimensions
Individuals were asked 9 questions about the triggers to utilise ICT for Health (see Section 7.1).
Factor analysis was performed with all these items. 24 From these items two factors have emerged: Individual oriented and Social and services oriented.

Empowerment dimensions
Empowerment, broadly understood as the development of personal involvement and responsibility, is one of the goals of prevention, promotion and protection in health. This definition assumes that responsibility is a more active form of control while competence refers to aptitudes or qualities that make it possible to be more autonomous and take a role in decision-making. Moreover, there are three different perspectives of personal empowerment, which seems to coexist with respect to Health:  An aptitude to comply with expert advice (professional perspective)  Self-reliance through individual choice (consumer perspective)  Social inclusion through the development of collective support (community perspective) With these premise, factor analysis was carried out with 18 questions (see Section 7.2) related with empowerment. 25 24 See Annex 5:  With all these items two underlying dimensions have emerged: control, which is related with responsibility; and competence; which is related with aptitudes and skills.

Barriers dimensions
Individuals were asked about 10 different types of barriers to utilise ICT for health (see Section 7.3).
Factor analysis was performed with all these items. 26 From these items two factors have emerged: Lack of confidence and Lack of Readiness.

Health information sources dimensions
Individuals were asked about the importance of 10 different information sources related with their health (see Section 6). These items were analysed using factor analysis. 27 This analysis revealed three underlining dimensions: Traditional media; Health professionals; and Social media.

Trust dimensions
Individuals were asked to what extend they trust 8 different actors to manage their personal health information (see Section 6). Factor analysis was carried out with all these items. 28 This analysis revealed two main dimensions: Companies Trust and Institutional Trust: Individuals were asked about 24 activities related with ICT for Health (see Section 8.1). Factor analysis was performed with all these items, 29 excluding individuals who were not aware of these 28 See Annex 5:

ICT for Health willingness dimensions
Individuals who answered they were not aware of the ICT for Health activities before mentioned and/or they never used were asked how likely it is that they would carry out these activities during the next year (see Section 8.2). These responses revealed their willingness to use ICT for Health. Factor analysis of these items was performed. 30 The results of this analysis revealed three dimensions: Web 2.0 uses; Services and Devices uses; Internet Health Information uses.

ICT for Health assessment dimensions
Individuals were asked about their preferences to evaluate a health website (see Section 9.2).
Factor analysis was carried out with seven items included in this question. 31 This analysis revealed two underling dimensions: Information and professionals and Interaction and organisations.

ICT for Health impact dimensions
Individuals were asked 12 questions about their perception on ICT for Health impact (see Section 10). These items were analysed using Factor analysis. 32 Results revealed two dimensions: Quality of healthcare and Healthy behaviours and Healthcare access

CONCLUSIONS
Factor analyses described in Section 11 were carried out following our 1.3 Conceptual framework: towards a social determinants of ICT for Health (see Section 1.3.) This analytical exercise has facilitated the synthesis of questionnaire items gathered into underlying dimensions or concepts. Figure 69 summarised all the dimensions: Structural and intermediary determinants of Health also produce different levels of ICT usage from Tech uses to Basis uses. This typology of uses represents an unequal access to ICT which will generate different levels of ICT for Health Access as well as different levels of willingness to use ICT for Health. Both blocks could be analysed in-depth detail. On the one hand, three different dimensions of willingness have been identified: Internet Health Information, Web 2.0 uses and Services and devices uses. These dimensions represent different level of complexity: from basic use of Internet Health information to the complex ecosystem of Services and devices. On the other hand, ICT for Health Access is comprised of three different blocks. Firstly, ICT for Health Motivation split up into three concepts with their related dimensions: Triggers (individual oriented and social and services oriented); Empowerment (competence oriented and control oriented) and Barriers (lack of confidence and lack of readiness). Secondly, ICT for Health Usage made up of Information and Communication usage and Services and Devices usage. Thirdly, ICT for Health Assessment tackled how individuals evaluate websites paying special attention to information and professionals involved and interaction and organisation involved.
The interrelationship between these three blocks gave rise to different level of Participatory Health through the individual and social use of ICT for Health and their impacts perceived. These impacts could be related with health management; healthcare demand or healthcare quality and, moreover, could have the potential to modify both structural and intermediary determinants and distribution of health and well-being.
All above mentioned unveiled the complexity of ICT for Health. To tackle this complexity, correlation analyses of all dimensions have been performed. The main results of these analyses are summarised in the following figure:  Unequal ICT readiness generates different levels of motivation. Individuals making more advance uses are triggered by the potential of ICT to facilitate social interaction and services related to health while individuals whose uses are basic or individual are triggered mainly by Internet health information for personal proposes. Furthermore, individuals with the lowest level of readiness (basic uses) and having reported more health problems lack confidence in the use of ICT for Health. Nevertheless, this lack of confidence is counterbalanced by a higher level of empowerment (competence oriented).
 Both ICT for Health usages (Services and Devices and Information and Communication) are specially driven by social and services triggers while individual triggers are only slightly correlated with Information and Communication usages, therefore less advanced uses.
 Both dimensions of Empowerment push ICT for Health usage. Individuals who are more competence-oriented are more inclined to Information and Communication usage while individuals who are more control-oriented are more likely to use Services and Devices. Thus individuals who feel more responsible for their health status are more likely to use Services and Devices while individuals who want to be more autonomous (competence refers to aptitudes or qualities that make it possible to be more autonomous) are more likely to utilise Information and Communication. If we consider individuals' education, age and health status it looks like Services and Devices are related with well-being and wellness practice, therefore with health prevention and promotion while Information and Communication are more related with illness, therefore with cure and independent living  All individuals using ICT for Health faced the same barriers; therefore lack of confidence and lack of readiness are not correlated significantly with ICT for Health usages. Nevertheless, lack of confidence is negatively correlated with the ICT for Health impact on the access dimension. Individuals need a certain level of confidence in ICT for Health to go beyond information and communication and engage with services such as RMT, Personal Health Records or videoconference consultation.
 The utilisation of Services and devices is strongly correlated with the perception that ICT would have an impact on both healthcare access and quality and healthy behaviours while the utilisation of Information and Communication is slightly correlated with Quality and healthy behaviours only.
 The number of health problems reported by individuals is only slightly correlated with Information and Communication Usage and it is unrelated to Services and devices utilisation. Therefore, individuals who could take more advantage of Services and devices, due to their health status, are more likely to be oriented towards information and communication usage only.
The study reported here reveals the potential of ICT for Health to promote active and healthy individuals and increase empowerment. Even though our findings relate to Internet users, it is worth pointing out that new health inequalities are emerging due to the impact of the "traditional determinants of heath" on ICT readiness.
Therefore, eInclusion policies related to ICT for Health are needed to ensure that individuals with low socio-economic status and more health problems are able to benefit from these types of technologies. These ICT for Health divides specially impact on the elderly. However, there is an opportunity for them to engage with the Information Society through ICT for Health due to the importance of health issues in their daily life.
The relationship between the different typologies of ICT readiness and ICT for Health Motivation and Impact reveal that:  Young individuals are already using this type of technologies mostly in relation with wellness and healthy life style. These uses enable an entire world of possibilities related with health promotion and prevention, especially considering that young individuals are heavy Web 2.0 users.
 Middle age individuals are also active users of ICT for Health acting as gatekeepers of this type of technologies within the household. Therefore these individuals could act as enablers for others i.e. both for the elderly and the young within households  The elderly are basically using ICT for Health for information and communication purposes. There is a gap between this type of use and services and devices uses which could be more effective in relation with cure and chronic conditions.
Individuals between 16-54 with chronic conditions, going under long-term treatment and with more than one health problems are more likely to use ICT for Health than individuals without these type of health problems. Individuals between 55-74 who are healthy are more likely to use ICT for Health, especially for Information and Communication, than individuals with worse health status. Therefore, in the short term, this group of individuals will be pushing for health systems to provide them with new solutions (services and devices) when they need to tackle a health problem. This pressure will increase during the next decade when middle age individuals become elderly. Therefore health systems are facing the challenge of having to promote further ICT innovation to answer these new demands. While this is an opportunity to improve both sustainability and efficiency of healthcare system, it is associated with a number of challenges linked to eHealth deployment.
However, during this transition, health systems cannot leave out the elderly, who are not active and healthy. This group of individuals, who are the current intensive users of healthcare systems, cannot be omitted. There is an opportunity to include them in the Information Society by improving ICT readiness and ICT for Health willingness and awareness.

ANNEXES Annex 1. Questionnaire and coding manual
We are currently conducting an International research study on behalf of the Institute for Prospective Technological Studies (IPTS), one of the seven scientific institutes of the European Commission's Joint Research Centre (JRC). The objective of the study is to analyze the use of Information and Communication Technologies (ICT), specially the Internet, for healthcare purposes.
In this regard, we would like to ask for 20 minutes of your time to complete this survey. We would very much appreciate your opinion.
Please rest assured the survey is anonymous and the data gathered strictly confidential.

Annex 2. Online panel providers
Cint is a privately owned software company that produces and sells market leading, innovate online research products for businesses, organizations and individuals involved in market research. The company specializes in SaaS, web-based software solutions offering efficient, user friendly online sample management and access, as well as online panel management products that are accessible worldwide 24/7. Headquartered in Stockholm, Sweden, Cint has offices across Europe and the USA. The company has an extensive list of clients and partners spanning most of the large market research groups, media and web-based companies, branding and advertising agencies, plus medium and small market research agencies and other organisations involved in market research. Cint's goal is to be the main provider of sampling solutions for online research, through efficient solutions that improve accuracy and reduce both time and cost. The company has launched a whole series of industry firsts that have dramatically reduced clients operating costs and raised standards in transparency and quality. Cint's products comply with ESOMAR, MRS, CASRO, MRA&ARF quality and personal integrity standards, as well as offering additional functions designed to enhance quality. All publicized panels operate within this controlled framework. Cint's Survey Quality Assurance Program ensures all projects by sample buyers are set up correctly and that the questionnaire is of the required standard. Since most data errors in research are made in the survey creation phase, Cint puts an emphasis on quality checking every survey reaching the Cint Panel Exchange network. All major and most minor languages issues are forced to be corrected before the project is launched. Cint's Quality Features:  Panellist rating: all panellists are scored by their level of survey activity. A high score shows active behaviour, while a lower score shows lower levels of activity. If a score drops to a certain agreed level, panel owners can use this scoring system to automatically clean their panels.
 Automatic cleaning: all panels in Cint Panel Exchange are automatically cleaned on hard bounces, where the email address is proven not to function.
 Random & Stratified Sampling: within the required targets, sample is randomly generated as well as being stratified by high, medium and low responders.
 Quarantine settings: Both panellists and panel owners can set the maximum number of surveys received.
 Exclusions: Panellists are automatically excluded from taking part in surveys in the same subject category or project regardless of panel they belong to.
 Re-invitations: Re-minder send outs to non-participants increase response and sampling efficiency.
 De-duping: Cint de-duping technology is able to detect and remove duplicates when inviting respondents to complete a specific survey.
 Professional panellists: At the registration stage personal information including name, address and other specific information is collected to assist in the validation process. Depending on incentive method used, unique identification data is required to redeem incentives such as: id number, home address and bank details.
 Panel Blending: Sample can be drawn from multiple panels simultaneously to reach hard to find target groups and eliminate source bias, and therefore reaching panellists with different motivation factors. It also allows users to benefit from selecting sample generated by different recruitment methods from CATI recruited panels to panels built from natural online communities, where members have a relationship with the panel owner's brand.
 Panellists survey rating: Panellist can rate every survey on length, language and logic and other errors in surveys. Panellist longevity is reached by respecting their feedback and their experience in taking surveys. This feedback can help buyers to improve the quality of their surveys, which in turn generates high quality results.
 Increased performance and security: As user of a SaaS system all users will get continuous updates and security patches and monitoring.
 Independent study on panel quality: Cint is a contributor to a major industry study on panel quality, conducted by Mkting Inc. The objective of the study is measure panel quality from different providers through asking panellists about their survey behaviour and to measure how buying behaviour results correlates between panels. The early findings are showing that a blended sample, using multiple panel sources, is a more reliable way to conduct online research.
Furthermore, CINT provides the following software and hardware security features:  All users require username and password secure logins  The ASP environment has been designed with security, high-availability and performance in mind.
 All servers, services and network are monitored 24/7 by both Cint and the hosting partner with operation teams on stand-by.

Annex 3. Pilot study
A pilot test was conducted to ensure the questionnaire functioned correctly. The test was carried out between July 1 and July 6, 2011. In the end, a total of 231 interviews were completed in Spain and the UK (116 in Spain and 115 in the UK) The reliability and validity of the questionnaire was tested. The reliability of the questionnaire was assessed in terms of consistency (using Cronbach's α (alpha) analysis as a coefficient of reliability). Cronbach's α (alpha) varies from zero to 1. Higher alpha values are more desirable. It is commonly accepted that a reliability of 0.70 or higher is required before using a tool. Table 11 shows Cronbach's α (alpha) values for the selected variables: To what extent do you agree with the following statements? 0,910 Valid The validity is the degree to which the questionnaire actually measures what is expected, or serves the purpose for which it has been prepared, and the analysis was carried out according to the content validity, construct validity, and criterion-related validity. After telephone contact with (approximately) 10% of the pilot study sample, the following conclusions were reached:  The questionnaire is rather long and repetitive due to the use of many scales  The questionnaire deals with an interesting topic that motivates the respondent to answer.
 There are no relevant problems of understanding In this sense, the only significant change remarkable in the final questionnaire in relation to the pilot questionnaire is:  The inclusion of the option "I was not aware of it" to avoid forcing an answer that would not reflect the real circumstances.